Executive, Data Operations

ROLE OVERVIEW

This role is responsible for supporting day-to-day data lake operations including pipelines monitoring and troubleshooting, data extraction and validation, process automation for operational excellence. The role involves close collaboration with cross-functional teams, and adherence to service-level agreements (SLAs) to support timely data-driven operations and pipelines executions. This role ensures accurate and reliable credit data by designing efficient processes, resolving inconsistencies, and maintaining high data quality to support robust credit scoring and informed business decisions

KEY RESPONSIBILITIES

Technical & Data Operations

• Perform adhoc and regular bulk data extraction based on business requirements and in line with SLAs. Such extraction may include both internal and external sources.
• Support and optimise Extract, Transform, Load (ETL) processes.
• Write Python scripts to automate routine data operation and data validation tasks.
• Handle data pipeline issues such as failures, slipped SLAs, incident escalations.
• Assist data engineering team and other users to deploy new pipelines or services for production.

Process Management & SLA Adherence

• Establish control and monitoring points to maintain runtime stability, data integrity, data security, and adhere to committed SLAs on daily basis.
• Identify and troubleshoot data quality issues proactively.
• Perform data lake capacity planning and utilization tracking.
• Maintain change controls with clear audit trails.
• Collaborate with cross-functional teams to gather data requirements and ensure timely delivery.

Documentation & Knowledge Management

• Document data workflows, automation scripts, and issue resolutions for future reference and process continuity.
• Maintain version controls and tracking for all pipelines.

WHAT DOES IT TAKE TO BE SUCCESSFUL

Qualifications

• Bachelor's Degree in Computer Science, Information Technology, or a related field.

Work Experience

• 1–2 years of experience in a data engineering, data operations, database management, or similar role.

Skills & Competencies

• Strong knowledge in SQL, NoSQL, Python, PySpark, DAX scripting, etc.
• Experience with data extraction from databases, APIs, or flat files.
• Familiarity with automation tools such as Airflow, cron jobs, or custom Python scripts.
• Ability to troubleshoot data issues.
• Ability to follow and manage SLAs for task completion and data delivery.

Attributes

• Strong attention to detail and commitment to data accuracy.
• Problem-solving mindset and ability to work independently.
• Excellent communication and time-management skills.
• Ability to work in a fast-paced, SLA-driven environment.